Staff Software Engineer- Foundation Model Inference
Join Databricks as a Staff Software Engineer to build LLM infrastructure for large-scale AI inference workloads.
Posted by employer 3 months ago
First seen on Joblaze 3 months ago
Last verified on the company career page 1 hour ago
Skills & Technologies
AI in the day-to-day
We build the infrastructure that enables our customers to serve, scale, and optimize frontier models with enterprise-grade reliability and performance.
Requirements
- Experience
- 8+ years
Not disclosed in this posting: work arrangement, visa sponsorship.
Joblaze summary
In this role, the Staff Software Engineer will focus on developing and optimizing the infrastructure that supports large-scale inference workloads for generative AI models. Key skills include expertise in distributed systems, scalable APIs, and cloud-native infrastructure, with a strong emphasis on real-time serving and ML infrastructure. This position is ideal for seasoned engineers with over eight years of experience who are eager to tackle complex challenges in AI at an enterprise level. The team operates at the cutting edge of AI technology, collaborating closely with various departments to enhance user experiences.
Joblaze insights
- Listed about 3 months ago — first seen on Joblaze July 24, 2026. Last confirmed on Databricks's careers page October 28, 2026.
- Salary band is in line with the typical range for AI/ML roles (median ~$190,000).
- Starts above 12% of 33 comparable staff ai/ml roles in United States that list PyTorch we track (median $230,000 across 18 companies).
- PyTorch appears in 14.5% of 282 comparable staff ai/ml roles in United States; Anthropic appears in 0.4% of 282 comparable staff ai/ml roles in United States.
Quick facts
- What's the salary range?
- Databricks lists $190,000–$265,000 for this role.
- How much experience is required?
- At least 8 years of relevant experience for this Staff Software Engineer- Foundation Model Inference role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Anthropic, Azure ML, GPT-OSS, Gemini, LLM, Llama.
- What seniority level is this role?
- Databricks targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Staff Software Engineer- Foundation Model Inference role at Databricks.
From the original posting
P-1930
At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer-obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
As part of the AI team, you'll build the platforms and products that power everything from data apps, AI agents, model training, model serving, and Vector Search. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We're building the products and infrastructure that power the next generation of AI.
The Foundation Model Inference team is the backbone of Databricks’ generative AI capabilities. We build the infrastructure that enables our customers to serve, scale, and optimize frontier models with enterprise-grade reliability and performance. Our Foundation Model APIs provide a unified platform that gives customers access to LLMs with the governance, flexibility, and scalability required for enterprise production workloads.
We are looking for high-agency engineers who are excited to work on powering model inference at enterprise scale.
Check out our recent blog post: Reliable LLM Inference at Scale
The impact you will have:
- Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama)
- Improve reliability, latency, and efficiency of distributed AI workloads
- Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences
- Shape how developers and data scientists build and interact with AI on Databricks
What we look for:
- 8+ years of experience in backend or infrastructure engineering
- Experience with distributed systems, scalable APIs, or cloud-native infrastructure
- Experience with real-time serving, ML infrastructure, or GPU orchestration
- Familiarity with service-oriented architecture, deployment pipelines, and system observability
Bonus points for:
- Exposure to platforms like SageMaker, Vertex AI, or Azure ML
- Contributions to OSS projects like MLflow, PyTorch, Ray, vLLM, SGLang
- Built developer platforms or internal tools supporting AI workflows
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
BenefitsStandard company text repeated across Databricks's postings is omitted here.